Convolutional networks can model the functional modulation of the MEG responses associated with feed-forward processes during visual word recognition by Marijn van Vliet, Oona Rinkinen, Takao Shimizu, Anni-Mari Niskanen, Barry Devereux, Riitta Salmelin

“…Through a few alterations to make the network more biologically plausible, we found an CNN architecture that can correctly simulate the behavior of three prominent responses, namely the type I (early visual response), type II (the ‘letter string’ response), and the N400m. …”
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Efficient Visual-Aware Fashion Recommendation Using Compressed Node Features and Graph-Based Learning by Umar Subhan Malhi, Junfeng Zhou, Abdur Rasool, Shahbaz Siddeeq

“…In this paper, we present the Visual-aware Graph Convolutional Network (VAGCN). …”
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Pansharpening via Multiscale Embedding and Dual Attention Transformers by Wensheng Fan, Fan Liu, Jingzhi Li

“…To solve this issue, we propose a pansharpening network based on multiscale embedding and dual attention transformers (MDPNet). …”
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A deep learning-driven multi-layered steganographic approach for enhanced data security by Yousef Sanjalawe, Salam Al-E’mari, Salam Fraihat, Mosleh Abualhaj, Emran Alzubi

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Dynamic graph attention network based on multi-scale frequency domain features for motion imagery decoding in hemiplegic patients by Yinan Wang, Yinan Wang, Lizhou Gong, Yang Zhao, Yewei Yu, Hanxu Liu, Xiao Yang

“…We validated the performance of MFF-DANet on the public PhysioNet dataset, achieving optimal decoding accuracies of 61.6% for within-subject case and 52.7% for cross-subject case. t-Distributed Stochastic Neighbor Embedding (t-SNE) visualization of the features demonstrates the effectiveness of each designed module, and visualization of the adjacency matrix indicates that the extracted spatial topological features have physiological interpretability.…”
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From Viewing to Structure: A Computational Framework for Modeling and Visualizing Visual Exploration by Kuan-Chen Chen, Chang-Franw Lee, Teng-Wen Chang, Cheng-Gang Wang, Jia-Rong Li

“…This study proposes a computational framework that transforms eye-tracking analysis from statistical description to cognitive structure modeling, aiming to reveal the organizational features embedded in the viewing process. Using the designers’ observation of a traditional Chinese landscape painting as an example, the study draws on the goal-oriented nature of design thinking to suggest that such visual exploration may exhibit latent structural tendencies, reflected in patterns of fixation and transition. …”
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Classification of Russian Texts by Genres Based on Modern Embeddings and Rhythm by Ksenia Vladimirovna Lagutina

“…Subsequently, these genres were classified best with the help of rhythm features and the neural network-classifier LSTM. Clustering and classifying texts by genre using ELMo and BERT embeddings made it possible to separate one genre from another with a small number of errors. …”
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KEDM: Knowledge-Embedded Diffusion Model for Infrared Image Destriping by Lingxiao Li, Xin Wang, Dan Huang, Yunan He, Zhuqiang Zhong, Qingling Xia

“…However, their output images often exhibit striped noise due to the nonuniform response of the detection system, which significantly affects image quality and visual fidelity. To address challenges such as incomplete stripe removal, potential loss of image details and textures, and the generation of artificial artifacts during destriping, we propose a novel stripe removal method based on a knowledge-embedded diffusion model (KEDM). …”
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Superior colliculus peri-saccadic field potentials are dominated by a visual sensory preference for the upper visual field by Ziad M. Hafed

“…Here, I asked whether peri-saccadic SC network activity can still reflect the SC’s visual sensitivity asymmetry, thus supporting recent evidence of sensory-related signals embedded within the SC’s motor bursts. …”
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Analisis Sentimen Kebijakan Penerapan Kurikulum Merdeka Sekolah Dasar dan Sekolah Menengah pada Media Sosial Twitter dengan Menggunakan Metode Word Embedding dan Long Short Term Me... by Alif Rizal Maulana, Satrio Hadi Wijoyo, Yusi Tyroni Mursityo

“…Arsitektur yang digunakan adalah Long Short-Term Memory Networks (LSTM). Metode yang digunakan untuk mempersiapkan data adalah word embedding dengan menggunakan layers embedding dari library TensorFlow. …”
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A Framework of Secured Embedding Scheme Using Vector Discrete Wavelet Transformation and Lagrange Interpolation by Maheswari Subramanian, Reeba Korah

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Visualization Methods for DNA Sequences: A Review and Prospects by Tan Li, Mengshan Li, Yan Wu, Yelin Li

“…Additionally, we summarize machine learning techniques applicable to sequence visualization, such as graph embedding methods and the use of convolutional neural networks (CNNs) for processing graphical representations. …”
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LIM: Lightweight Image Local Feature Matching by Shanquan Ying, Jianfeng Zhao, Guannan Li, Junjie Dai

“…To address this challenge, we propose LIM, a lightweight image local feature matching network designed for computationally constrained embedded systems. …”
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Quality Analysis of Massive High-Definition Video Streaming in Two-Tiered Embedded Camera-Sensing Systems by Joongheon Kim, Eun-Seok Ryu

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Auto-embedding transformer under multi-source information fusion for few-shot fault diagnosis by Bo Wang, Shuai Zhao, Qian Zhao, Yang Bai

“…To address these challenges, we propose a novel auto-embedding transformer named EDformer, tailored for multi-source information under few-shot fault diagnosis. …”
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VISUAL AND INFORMATION EFFICIENCY OF EDUCATIONAL INSTITUTIONS' WEB RESOURCES by Olha Holovko

“…The research objectives included a theoretical study of the problem of the visual and technical design of educational websites as an indicator of their informational effectiveness, as well as an analysis of specific examples of educational web resources in terms of their visual and technical design and informational effectiveness. …”
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Vision Transformer Embedded Feature Fusion Model with Pre-Trained Transformers for Keratoconus Disease Classification by Md Fatin Ishrak, Md Maruf Rahman, Md Imran Kabir Joy, Anna Tamuly, Salma Akter, Dewan M. Tanim, Shahajada Jawar, Nayeem Ahmed, Md Sadekur Rahman

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Carrier-independent deep optical watermarking algorithm by Hao CHEN, Feng WANG, Weiming ZHANG, Nenghai YU

“….), so that the carrier carries the identification information but does not affect the normal use of the carrier.The common digital watermark embedding scheme is to embed the watermark information by modifying the carrier via specific algorithms.In the actual application scenarios, there are many images or objects to be protected (such as art paintings, etc.) that are not allowed to be modified.Based on this background, a new carrier-independent deep optical watermarking algorithm was proposed, which can realize watermark information embedding without modifying the original carrier and achieve the purpose of copyright protection.Specifically, a new watermark template expression scheme at the embedding end was proposed, which expressed the watermark information by visible light modulation.By analyzing the visual system of human eyes, a watermark template pattern based on alternating projection was proposed to embed the watermark information, which made the embedding process neither require modification of the original carrier nor affect the visual senses of human eyes.At the extraction end, a watermark extraction network based on residual connection was designed, and the captured watermarked images were fed into this network after perspective transformation to extract the watermark information.The experiments were conducted under various conditions and comparisons with three baseline algorithms were made.The experimental results show that the proposed algorithm generates watermarked images with less visual distortion and is robust to the ＆quot;projecting-shooting＆quot; process.The watermark extraction network has high accuracy in extracting watermark information at different distances, angles and illumination conditions, and has certain advantages over other general networks.…”
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Medical Image Retrieval Based on Ensemble Learning using Convolutional Neural Networks and Vision Transformers by Ahmed Yahya, Dalya Khaled, Waleed Al-Azzawi, Tawfeeq Alghazali, H. Sabah Jabr, R. Madhat Abdulla, M. Kadhim Abbas Al-Maeeni, N. Hussin Alwan, S. Saad Najeeb, Kh. T. Falih

“…One of the most serious challenges that require special attention is the representational quality of the embeddings generated by the retrieval pipelines. These embeddings should include global and local features to obtain more useful information from the input data. …”
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Multi-photon neuron embedded bionic skin for high-precision complex texture and object reconstruction perception research by Hongyu Zhou, Chao Zhang, Hengchang Nong, Junjie Weng, Dongying Wang, Yang Yu, Jianfa Zhang, Chaofan Zhang, Jinran Yu, Zhaojian Zhang, Huan Chen, Zhenrong Zhang, Junbo Yang

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